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CORRECTION article

Front. Oncol., 21 October 2025

Sec. Cancer Epidemiology and Prevention

Volume 15 - 2025 | https://doi.org/10.3389/fonc.2025.1715188

This article is part of the Research TopicAdvanced Machine Learning Techniques in Cancer Prognosis and ScreeningView all 12 articles

Correction: Evaluation of recent lightweight deep learning architectures for lung cancer CT classification

MennaAllah Mahmoud*&#x;MennaAllah Mahmoud1*†Yanhua Wen&#x;Yanhua Wen1†Xiaohuan PanXiaohuan Pan2Yuling LiufuYuling Liufu1Yubao Guan*Yubao Guan1*
  • 1Radiology Department, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
  • 2Radiology Department, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China

A Correction on
Evaluation of recent lightweight deep learning architectures for lung cancer CT classification

By Mahmoud M, Wen Y, Pan X, Liufu Y and Guan Y (2025). Front. Oncol. 15:1647701. doi: 10.3389/fonc.2025.1647701

Author “Yanhua Yen” was erroneously omitted as equal contributing author. The original version of this article has been updated.

The correct author list reads:

“MennaAllah Mahmoud1*†, Yanhua Wen1†, Xiaohuan Pan2, Yuling Liufu1 and Yubao Guan1*

The original version of this article has been updated.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: deep learning, pre-trained models, lightweight models, lung cancers, computed tomography

Citation: Mahmoud M, Wen Y, Pan X, Liufu Y and Guan Y (2025) Correction: Evaluation of recent lightweight deep learning architectures for lung cancer CT classification. Front. Oncol. 15:1715188. doi: 10.3389/fonc.2025.1715188

Received: 29 September 2025; Accepted: 13 October 2025;
Published: 21 October 2025.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2025 Mahmoud, Wen, Pan, Liufu and Guan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: MennaAllah Mahmoud, bWVubmEyMmFAeWFob28uY29t; Yubao Guan, eXViYW9ndWFuQDE2My5jb20=

These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.